artificialintelligence

January 11, 2021

What Data Scientists should know about Multi-output and Multi-label Training

Multi-output Machine Learning — MixedRandomForest Introduction Multi-output learning subsumes many learning problems in multiple disciplines and deals with complex decision-making in many real-world applications. It has a multivariate nature and the multiple outputs may have complex interactions, architected to be handled by structured inference. The output values have diverse data types, depending on the type of ML problem. For example, 0/1 based Binary output values can refer to multi-label classification problem. Nominal output values to […]

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Retail

April 29, 2020

Traditional vs Deep Learning Algorithms used in BlockChain in Retail Industry — III

SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN Introduction In continuation to my previous blogs, “Traditional vs Deep Learning in Retail Industry” and “Deep Learning Vs Deep Reinforcement Learning Algorithms in Retail Industry” this blog highlights on different ML algorithms used in blockchain transactions with a special emphasis on bitcoins in retail payments. This blog is structured as follows: Overview of introduction of blockchain and its predominant in retail industry. Different traditional algorithms(SecureSVM, Bagging, Boosting,Random Forest, Clustering-K-Means, Agglomerative) vs deep learning algorithms […]

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AI Trends

April 29, 2020

Facts and Figures on how AI is impacting the economy and shaping the GDP worldwide

Summarization of Research Insights from Emerj, Harvard Business Review, MIT Sloan, and Mckinsey Introduction Wall Street, venture capitalists, technology executives, data scientists — all have important reasons to understand the growth and opportunity in the artificial intelligence market to understand business growth and opportunities from funds invested in AI and analytics. Indeed, the growth of AI, continuing research, development of easier open source libraries and applications in small to large scale industries are sure to […]

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Neural Networks with push button, AI for all

AI Research

April 27, 2020

Neural Networks with push button, AI for all

Neural Architecture Search with NASBench from Google Research— Can we design network architectures automatically, instead of relying on expert experience and knowledge? Motivation Recent advances in neural architecture search (NAS) has vastly increased demand of high-end servers having tremendous computational resources. As the cost of maintaining high-end servers is high, it becomes inaccessible to students and researchers. As a result, it creates a system limitation when students and researchers are not able to reproduce experiments […]

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AI and Deep learning Algorithms in Telecom

AI Research, Deep Learning, Telecom, Traditional Machine Learning

April 27, 2020

Traditional vs Deep Learning Algorithms in the Telecom Industry — Cloud Architecture and Algorithm Categorization

Google Cloud Architecture for Machine Learning Algorithms in the Telecom Industry Introduction The unprecedented growth of mobile devices, applications and services have placed the utmost demand on mobile and wireless networking infrastructure. Rapid research and development of 5G systems have found ways to support mobile traffic volumes, real-time extraction of fine-grained analytics, and agile management of network resources, so as to maximize user experience. Moreover inference from heterogeneous mobile data from distributed devices experiences challenges due to […]

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